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"With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost efficient manner.Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions."

"Penelitian mengenai aplikasi m-Health mengungkapkan bahwa privasi dan keamanan masih menjadi isu yang penting pada aplikasi tersebut. Indonesia sendiri masih sering dihadapkan dengan insiden kebocoran data pengguna pada aplikasi m-Health. Oleh karena itu, penelitian ini bertujuan untuk mengevaluasi kepatuhan kebijakan privasi berdasarkan hukum yang berlaku, serta menganalisis sejauh mana aplikasi m-Health di Indonesia melindungi privasi pengguna dan menjaga keamanan aplikasinya ditinjau dari sisi teknis. Dilakukan penilaian kepatuhan kebijakan privasi terhadap Undang-Undang Nomor 27 Tahun 2022 tentang Pelindungan Data Pribadi (UU PDP) dan analisis keamanan aplikasi secara statis dan dinamis dengan menggunakan tools, seperti MobSF dan Fiddler (proxy), untuk mengidentifikasi celah keamanan berdasarkan standar yang ada, dalam hal ini CWE (Common Weakness Enumeration). Hasil yang didapatkan menunjukkan bahwa skor penilaian kepatuhan kebijakan privasi tertinggi hanya mencapai 65% dan setiap aplikasi setidaknya diduga memiliki satu kelemahan pada fitur keamanan yang diimplementasikan. Dengan begitu, dapat disimpulkan bahwa kebijakan privasi aplikasi m-Health di Indonesia belum sepenuhnya sesuai dengan apa yang ditetapkan dalam UU PDP dan masih banyak celah keamanan pada aplikasi m-Health yang dapat dieksploitasi.

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The research on m-Health applications reveals that privacy and security remain significant concerns in these applications. Indonesia itself frequently faces incidents of user data breaches in m-Health applications. Therefore, this study aims to evaluate compliance with privacy policies based on applicable law and analyze the extent to which m-Health applications in Indonesia protect user privacy and maintain application security from a technical perspective. The assessment includes evaluating privacy policy compliance with Undang-Undang Nomor 27 Tahun 2022 tentang Pelindungan Data Pribadi (UU PDP) and conducting static and dynamic application security analysis using tools such as MobSF and Fiddler (proxy). This analysis aims to identify security vulnerabilities based on a standard, specifically Common Weakness Enumeration (CWE). The results indicate that the highest privacy policy compliance score reaches only 65%, and each application is suspected of having at least one weakness in the implemented security features. Consequently, it can be concluded that the privacy policies of m-Health applications in Indonesia are not fully aligned with the provisions of the UU PDP. Additionally, there are still numerous security vulnerabilities in m-Health applications that could be exploited."

"Penelitian ini bertujuan untuk menilai efektivitas early warning score terhadap kejadian henti jantung pasien di instalasi rawat inap rumah sakit tingkat IV TNI AD dr.Bratanata Jambi Tahun 2019. Penelitian dilaksanakan di bulan Desember 2018 sampai April 2019 di instalasi rawat inap dengan pendekatan kualitatif dengan metode studi kasus. Teknik untuk memperoleh data adalah dengan wawancara mendalam, telaah dokumen, dan observasi langsung. Hasil penelitian menunjukkan adanya kejadian yang tidak diharapkan berupa kejadian henti jantung mengarahkan kepada penerapan early warning score yang belum optimal. Ketidakpatuhan terhadap pengisian, pengkajian, dan pengaktifan protokol early warning score di lapangan antara lain dipengaruhi oleh maldistribusi perawat, beban kerja perawat yang tidak sesuai dengan kompetesinya, pengetahuan perawat, dan komunikasi antara perawat dengan dokter. Hambatan penerapan EWS di lapangan antara lain ketidaksesuaian jumlah perawat berbanding dengan pasien, beban kerja perawat di luar pelayanan kesehatan, dan kurangnya pengetahuan dari staf mengenai penurunan kondisi klinis pasien. Hal ini bermuara kepada standar operasional prosedur yang belum lengkap dan penyusunan pola ketenagaan yang masih belum efektif dan efisien, juga monitoring-evaluasi dan pelatihan berkesinambungan yang belum berjalan dengan baik sehingga implementasi early warning score tidak optimal. Rekruitmen pegawai sesuai dengan kompetensi dan profesionalitas, pembuatan kebijakan yang menggabungkan pola kebijakan top-down dan bottom-up, pengaturan ulang penempatan sumber daya perawat, pendidikan dan pelatihan berkelanjutan merupakan upaya yang dapat meningkatkan keberhasilan implementasi early warning score.

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This study aims to assess the effectiveness of the application of early warning score on patients cardiac arrest events in the inpatient at installation level IV Army Hospital Dr.Bratanata Jambi in 2019. The study was conducted in December 2018 to April 2019 in inpatient installations with a qualitative approach with a case study method. The technique for obtaining data is through in-depth interviews, document review, and direct observation. The results of the study show that the occurrence of adverse events such as cardiac arrests lead to an unoptimal implementation of an early warning score. Nurses noncompliance in filling, assessing and activating early warning score protocol in the field is influenced by nurses maldistribution, nurses workloads that are not in accordance with their competencies, nurses knowledge, and communication between nurses and doctors. Barriers to the application of EWS in the field include the mismatch of the number of nurses compared to patients, the workload of nurses outside of health services, and the lack of knowledge from staff regarding the decline in the patients clinical condition. This leads to incomplete operational standard procedures and the formulation of work patterns that are still ineffective and inefficient, as well as ongoing evaluations and training that have not run well so that the implementation of an early warning score is not optimal. Employee recruitment in accordance with competence and professionalism, policy making that combines topdown and bottom-up policy patterns, rearranging the placement of nurse resources, continuing education and training is an effort that can increase the success of the implementation of an early warning score."

"This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference, eHealth 2010, held in Casablanca, Morocco, in December 2010. The 30 revised full papers presented along with 12 papers from 2 collocated workshops were carefully reviewed and selected from 70 submissions in total and cover a wide range of topics including web intelligence, privacy, trust and security, ontologies and knowledge management, eLearning and education, Web 2.0 and online communications of practice, and performance monitoring and evaluation frameworks for healthcare."